Research On Vehicle Path Tracking Control Strategy For Horizontal And Longitudinal Aspects

With the development of intelligent transportation networks,Intelligent vehicles became one of the most meaningful members.the trajectory tracking problem is closely related to intelligent transportation networks.It is helps us optimize the safety of driving availably.And it helps enhance the life comfort level.The vehicle path tracking problem includes two main parts.On the one hand,it is the longitudinal control of vehicle speed.Beyond that,it is the lateral control of stability.Finally,this paper combined horizontal control and vertical control.The vehicle can follow the expected path stably and accurately.In view of the above challenges,this article will apply many different control methods to study the challenges of this paper.And the simulation experiment verifies the control results.In the design of the longitudinal controller,the control objective is mainly to accelerate or decelerate adjustment in the driving process according to the difference between the actual speed and the expected speed,so that the vehicle speed is as close as possible to the expected speed given,that is,the vehicle speed changes according to the given expected speed curve.In the research process,PID control is selected as the main controller,and fuzzy control is involved in the parameter tuning of PID.Finally,fuzzy PID is adopted to control the longitudinal velocity of vehicle.In order to verify the effectiveness of the controller,simulation experiments are carried out under acceleration,deceleration and variable speed conditions.The simulation results show that the longitudinal controller can accurately and stably control the actual vehicle speed to follow the expected speed curve.In the research process of the lateral controller,the dynamic model of the vehicle is first established as the prediction model of the lateral controller.The magic formula tire model was used for pure slip and pure sideslip simulation tests,which laid the foundation for the subsequent formulation of controller constraint conditions.In the design process of the lateral controller,the model predictive control algorithm is used to realize the vehicle path tracking process.Firstly,the vehicle model is linearized and discretized to obtain a linear time-varying model.On the basis of this model,the corresponding formula is derived,and the objective function of the algorithm is designed according to the control objective to ensure the safety,stability and accuracy of the control.In order to obtain better control effect,the constraint conditions of the input,the centroid sideslip angle and the tire sideslip angle are designed,and the vehicle path tracking process is carried out on the premise of ensuring the vehicle stability.Finally,verification is carried out under different simulation conditions.Different operating parameters include speed setting and road adhesion coefficient setting.The simulation trajectory includes straight path trajectory,singleline path trajectory and double-line path trajectory to verify the effect of the controller.The simulation test of the lateral controller is carried out under the condition of constant vehicle speed,but considering the actual situation,the vehicle speed is constantly changing with the change of the external environment,especially under the condition of driving on the curved road.Therefore,the vehicle is finally controlled horizontally and vertically.The longitudinal controller adjusts the longitudinal velocity of the vehicle when it passes through the curved road through the road curvature and the road surface adhesion coefficient.The transverse controller provides various constraints for vehicle stability,and the simulation experiment is carried out to verify the effectiveness of the controller.The simulation results show that the vehicle can follow the given path model more accurately and stably under the combined control of the two controllers.The path tracking control model proposed in this paper has good control accuracy and stability.